Research on Adaptive Identification Systems to Estimate Dynamic Behaviors of Moving Objects

在本研究中，我们导出了用于估计和控制非线性系统动态行为的自适应参数调整律。采用满足Riccati方程的动态误差系统代替了满足Lurie方程的动态误差系统，并利用类似σ-修正的参数调整律证明了误差系统的有界性。利用所提出的方法设计了具有未知非线性输入的未知稳定对象的模糊自适应辨识器，并针对具有两输入两输出的球盘装置设计了模糊辨识器和控制器。球盘系统是由Tequipment公司生产的教育套件，它由一个在其中心旋转的板组成，这样可以在两个垂直的方向上操纵板的斜率，并且具有测量球位置的智能视觉系统。首先，给出了球盘系统的非线性模型，即模糊基函数展开的模糊逼近器。得到的模糊模型包含系统参数的乘积，回归量信号由模糊基函数组成。其次，为了估计模糊模型中的未知系统参数，将植物参数的线性辨识器添加到输入非线性的模糊辨识器中。最后，通过MATLAB仿真和实验对所提模糊辨识器的性能进行了研究。

In this research, we derived the adaptive parameter adjustment law to estimate and control of dynamic behavior of nonlinear systems. We used a dynamic error system which satisfied a Riccati equation instead of the Lurie' equations, and showed the boundedness of the error system using σ-modification-like parameter adjustment law. Using the proposed We desinged the fuzzy adaptive identifier for unknown stable plants with unknown input nonlinearities, and designed a fuzzy identifier and a controller for the ball-plate apparatus which has two inputs and two outputs. The ball-plate system is the educational kit produced by Tequipment Inc., which consists of a plate pivoted at its center such that the slope of the plate can be manipulated in two perpendicular directions and which has the intelligent vision system for measurement of a ball position. First, a nonlinear model, called the fuzzy approximator expanded by the fuzzy basis functions, of the ball-plate system is given. The obtained fuzzy model contains the product of the system parameters and regressor signals consist of the fuzzy basis functions. Next, to estimate the unknown system parameters in the fuzzy model, the linear identifier for plant parameters is added to the fuzzy identifier for input nonlinearities. Finally, the performance of the proposed fuzzy identifier is investigated by the MATLAB simulation and the experiment.